The invention relates generally to image processing and image analysis. More specifically, the present technique relates to image analysis for quantifying expression levels and distribution of proteins or other biological markers within a biological sample.
Quantifying expression levels of proteins with subcellular resolution is useful in many applications ranging from biomarker discovery, pharmaceutical research, and systems biology to treatment planning. Quantitation of target molecules at subcellular resolution enables direct association of the expression levels with the localized protein pathways. Large-scale prediction and correlation studies can be designed based on automatically quantifying expression patterns with known clinical outcomes
The number of markers that are related to the prognosis, drug response, survival time, and disease recurrence has been increasing steadily, and there is a shifting trend towards personalized therapeutics in the design of new drugs and specific qualifying criteria for drug use. Tissue micro arrays have rapidly become an essential tool to increase throughput for validation, and provide proteomic discovery platforms by surveying the expression profile of tumor samples.
Generally, tissue micro arrays may involve large-scale numbers of samples from either a single patient source or a number of patient sources. These samples may be stained with imaging probes that have binding specificity for certain markers, i.e., proteins, of interest. After staining, images of the samples may be acquired and the expression of the marker, or markers, of interest in each sample may be evaluated based on the binding of the probe to the marker.
Current techniques for estimating protein expression in immunohistochemically stained samples involve intensity or ratio-based techniques. These techniques generally provide a single score after evaluation of the image. However, such techniques do not differentiate between abundant low expression levels and scarce high expression levels of the markers of interest. For example, often images are evaluated to determine the percent of cells that have any expression, regardless of intensity, of the marker of interest. If this number is greater than a certain threshold, the image is scored as a positive. Because the intensity is not evaluated, strongly stained images are scored similarly to weakly stained images if the percent of expressing cells is the same. In other techniques, the total immunofluorescence of the image in the range of the probe's fluorescence is used to determine a score for the expression of the marker of interest. However, total immunofluorescence is determined by both the strength of expression as well as the abundance of the marker. A single score does not provide information about these two contributing factors. Therefore, such techniques fail to determine whether a marker exhibits abundant low expression levels or scarce high expression levels.